U.S. patent application number 12/253815 was filed with the patent office on 2009-04-16 for capturing symbolic information from documents upon printing.
Invention is credited to Berna Erol, Jamey Graham, Jonathan J. Hull, Jorge Moraleda, Ichiro Sakikawa, Daniel G. Van Olst.
Application Number | 20090100334 12/253815 |
Document ID | / |
Family ID | 40535386 |
Filed Date | 2009-04-16 |
United States Patent
Application |
20090100334 |
Kind Code |
A1 |
Hull; Jonathan J. ; et
al. |
April 16, 2009 |
Capturing Symbolic Information From Documents Upon Printing
Abstract
An MMR system for publishing comprises a plurality of mobile
devices, an MMR gateway, an MMR matching unit, and an MMR
publisher. A computer includes a document authoring application,
plug-in, and printer driver. The MMR matching unit receives an
image query from the MMR gateway and sends it to one or more of the
recognition units to identify a result including a document, the
page and the location on the page. The list of results and links
are sent back to the MMR gateway for presentation on the mobile
device. The present invention also includes a number of novel
methods including a method for capturing symbolic information from
documents and for capturing printer dll functions.
Inventors: |
Hull; Jonathan J.; (San
Carlos, CA) ; Erol; Berna; (San Jose, CA) ;
Graham; Jamey; (San Jose, CA) ; Moraleda; Jorge;
(Menlo Park, CA) ; Sakikawa; Ichiro; (Tokyo,
JP) ; Van Olst; Daniel G.; (San Francisco,
CA) |
Correspondence
Address: |
RICOH/FENWICK
SILICON VALLEY CENTER, 801 CALIFORNIA STREET
MOUNTAIN VIEW
CA
94041
US
|
Family ID: |
40535386 |
Appl. No.: |
12/253815 |
Filed: |
October 17, 2008 |
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Patent Number |
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11461049 |
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11461109 |
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11827530 |
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12059583 |
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12060194 |
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12060206 |
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11776520 |
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11776510 |
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11776530 |
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11776520 |
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12210511 |
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Current U.S.
Class: |
715/255 |
Current CPC
Class: |
G06F 16/93 20190101;
G06K 9/00979 20130101; G06F 16/583 20190101; G06K 9/00463 20130101;
G06F 16/955 20190101 |
Class at
Publication: |
715/255 |
International
Class: |
G06F 17/00 20060101
G06F017/00 |
Claims
1. A method of capturing symbolic information in a document,
comprising: modifying data sent to a printer driver uniquely
identifying symbolic information in an electronic document without
altering a layout of the electronic document; saving a target
associated with the symbolic information as a symbolic hotspot
file; in response to a print command, determining coordinates for
the symbolic information for saving as a page description file; and
merging the page description file with the symbolic hotspot file to
create a merged hotspot file.
2. The method of claim 1, wherein modifying further comprises
inserting fiducial marks into the data.
3. The method of claim 2, wherein the fiducial marks comprise a
special font with no glyphs.
4. The method of claim 1, wherein a plug-in to a document authoring
application provides instructions for modifying the data and saving
the target.
5. The method of claim 4, wherein the document authoring
application is selected from word, acrobat, internet explorer, and
quark xpress.
6. The method of claim 1, wherein the symbolic information is a
URL.
7. A computer readable storage medium storing instructions for
executing by a processor, the instructions comprising: modifying
data sent to a printer driver uniquely identifying symbolic
information in an electronic document without altering a layout of
the electronic document; saving a target associated with the
symbolic information as a symbolic hotspot file; in response to a
print command, determining coordinates for the symbolic information
for saving as a page description file; and merging the page
description file with the symbolic hotspot file to create a merged
hotspot file.
8. The computer readable storage medium of claim 7, wherein
modifying further comprises inserting fiducial marks into the
data.
9. The computer readable storage medium of claim 8, wherein the
fiducial marks comprise a special font with no glyphs.
10. The computer readable storage medium of claim 7, wherein a
plug-in to a document authoring application provides instructions
for modifying the data and saving the target.
11. The computer readable storage medium of claim 10, wherein the
document authoring application is selected from word, acrobat,
internet explorer, and quark xpress.
12. The computer readable storage medium of claim 7, wherein the
symbolic information is a URL.
13. A method performed by a print capture dynamically linked
library, comprising: intercepting commands intended for a printer
graphics dynamically linked library; performing received commands
on a memory buffer; and in response to a command to print a page,
saving a raster image of the page.
14. The method of claim 13, further comprising creating a printer
device monitoring object in response to a call to create a physical
device instance.
15. The method of claim 13, further comprising creating the memory
buffer as a secondary surface.
16. The method of claim 13, further comprising, in response to the
command to print the page, saving a symbolic description of content
on the page.
17. The method of claim 13, further comprising monitoring calls
received at the print capture dynamically linked library.
18. The method of claim 17, further comprising passing on the
received calls to the printer graphics dynamically linked
library.
19. The method of claim 13, wherein the print capture dynamically
linked library is a forwarding dynamically linked library.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation in part of U.S. patent
application Ser. No. 11/461,017, titled "System And Methods For
Creation And Use Of A Mixed Media Environment," filed Jul. 31,
2006, attorney docket no. 20412-11713; U.S. patent application Ser.
No. 11/461,279, titled "Method And System For Image Matching In A
Mixed Media Environment," filed Jul. 31, 2006, attorney docket no.
20412-11714; U.S. patent application Ser. No. 11/461,286, titled
"Method And System For Document Fingerprinting Matching In A Mixed
Media Environment," filed Jul. 31, 2006, attorney docket no.
20412-11715; U.S. patent application Ser. No. 11/461,294, titled
"Method And System For Position-Based Image Matching In A Mixed
Media Environment," filed Jul. 31, 2006, attorney docket no.
20412-11716; U.S. patent application Ser. No. 11/461,300, titled
"Method And System For Multi-Tier Image Matching In A Mixed Media
Environment," filed Jul. 31, 2006, attorney docket no. 20412-11717;
U.S. patent application Ser. No. 11/461,126, titled "Integration
And Use Of Mixed Media Documents," filed Jul. 31, 2006, attorney
docket no. 20412-11718; U.S. patent application Ser. No.
11/461,143, titled "User Interface For Mixed Media Reality," filed
Jul. 31, 2006, attorney docket no. 20412-11719; U.S. patent
application Ser. No. 11/461,268, titled "Authoring Tools Using A
Mixed Media Environment," filed Jul. 31, 2006, attorney docket no.
20412-11720; U.S. patent application Ser. No. 11/461,272, titled
"System And Methods For Creation And Use Of A Mixed Media
Environment With Geographic Location Information," filed Jul. 31,
2006, attorney docket no. 20412-11721; U.S. patent application Ser.
No. 11/461,064, titled "System And Methods For Portable Device For
Mixed Media System," filed Jul. 31, 2006, attorney docket no.
20412-11722; U.S. patent application Ser. No. 11/461,075, titled
"System And Methods For Use Of Voice Mail And Email In A Mixed
Media Environment," filed Jul. 31, 2006, attorney docket no.
20412-11723; U.S. patent application Ser. No. 11/461,090, titled
"System And Method For Using Individualized Mixed Document," filed
Jul. 31, 2006, attorney docket no. 20412-11724; U.S. patent
application Ser. No. 11/461,037, titled "Embedding Hot Spots In
Electronic Documents," filed Jul. 31, 2006, attorney docket no.
20412-11725; U.S. patent application Ser. No. 11/461,085, titled
"Embedding Hot Spots In Imaged Documents," filed Jul. 31, 2006,
attorney docket no. 20412-11726; U.S. patent application Ser. No.
11/461,091, titled "Shared Document Annotation," filed Jul. 31,
2006, attorney docket no. 20412-11727; U.S. patent application Ser.
No. 11/461,095, titled "Visibly-Perceptible Hot Spots In
Documents," filed Jul. 31, 2006, attorney docket no. 20412-11728;
U.S. patent application Ser. No. 11/466,414, titled "Mixed Media
Reality Brokerage Network and Methods of Use," filed Jul. 31, 2006,
attorney docket no. 20412-11729; U.S. patent application Ser. No.
11/461,147, titled "Data Organization and Access for Mixed Media
Document System," filed Jul. 31, 2006, attorney docket no.
20412-11730; U.S. patent application Ser. No. 11/461,164, titled
"Database for Mixed Media Document System," filed Jul. 31, 2006,
attorney docket no. 20412-11731; U.S. patent application Ser. No.
11/461,024, titled "Triggering Actions With Captured Input In A
Mixed Media Environment," filed Jul. 31, 2006, attorney docket no.
20412-11732; U.S. patent application Ser. No. 11/461,032, titled
"Triggering Applications Based On A Captured Text In A Mixed Media
Environment," filed Jul. 31, 2006, attorney docket no. 20412-11733;
U.S. patent application Ser. No. 11/461,049, titled "Triggering
Applications For Distributed Action Execution And Use Of Mixed
Media Recognition As A Control Input," filed Jul. 31, 2006,
attorney docket no. 20412-11734; U.S. patent application Ser. No.
11/461,109, titled "Searching Media Content For Objects Specified
Using Identifiers," filed Jul. 31, 2006, attorney docket no.
20412-11735; U.S. patent application Ser. No. 11/827,530, titled
"User Interface For Three-Dimensional Navigation," filed Jul. 11,
2007, attorney docket no. 20412-13180; U.S. patent application Ser.
No. 12/060,194, titled "Document-Based Networking With Mixed Media
Reality," filed Mar. 31, 2008, attorney docket no. 20412-13396;
U.S. patent application Ser. No. 12/059,583, titled "Invisible
Junction Feature Recognition For Document Security Or Annotation,"
filed Mar. 31, 2008, attorney docket no. 20412-13397; U.S. patent
application Ser. No. 12/060,198, titled "Document Annotation
Sharing," filed Mar. 31, 2008, attorney docket no. 20412-13901;
U.S. patent application Ser. No. 12/060,200, titled "Ad Hoc
Paper-Based Networking With Mixed Media Reality," filed Mar. 31,
2008, attorney docket no. 20412-13902; U.S. patent application Ser.
No. 12/060,206, titled "Indexed Document Modification Sharing With
Mixed Media Reality," filed Mar. 31, 2008, attorney docket no.
20412-13903; U.S. patent application Ser. No. 12/121,275, titled
"Web-Based Content Detection In Images, Extraction And
Recognition," filed May 15, 2008, attorney docket no. 20412-14041;
U.S. patent application Ser. No. 11/776,510, titled "Invisible
Junction Features For Patch Recognition," filed Jul. 11, 2007,
attorney docket no. 20412-12829; U.S. patent application Ser. No.
11/776,520, titled "Information Retrieval Using Invisible Junctions
and Geometric Constraints," filed Jul. 11, 2007, attorney docket
no. 20412-13136; U.S. patent application Ser. No. 11/776,530,
titled "Recognition And Tracking Using Invisible Junctions," filed
Jul. 11, 2007, attorney docket no. 20412-13137; U.S. patent
application Ser. No. 11/777,142, titled "Retrieving Documents By
Converting Them to Synthetic Text," filed Jul. 12, 2007, attorney
docket no. 20412-12590; and U.S. patent application Ser. No.
11/624,466, titled "Synthetic Image and Video Generation From
Ground Truth Data," filed Jan. 18, 2007, attorney docket no.
20412-12219; U.S. patent application Ser. No. 12/210,511, titled
"Architecture For Mixed Media Reality Retrieval Of Locations And
Registration Of Images," filed Sep. 15, 2008; U.S. patent
application Ser. No. 12/510,519, titled "Automatic Adaption Of An
Image Recognition System To Image Capture Devices," filed Sep. 15,
2008; U.S. patent application Ser. No. 12/510,532, titled
"Computation Of A Recognizability Score (Quality Predictor) For
Image Retrieval," filed Sep. 15, 2008; U.S. patent application Ser.
No. 12/510,540, titled "Combining Results Of Image Retrieval
Processes" filed Sep. 15, 2008; all of which are incorporated by
reference herein in their entirety.
BACKGROUND OF THE INVENTION
[0002] 1. Field of the Invention
[0003] The invention relates to techniques for creating a mixed
media document that is formed from at least two media types, and
more particularly, to registering an image and other data in a
Mixed Media Reality (MMR) system that uses printed media in
combination with electronic media to retrieve mixed media documents
and associated advertisements.
[0004] 2. Background of the Invention
[0005] Document printing and copying technology has been used for
many years in many contexts. By way of example, printers and
copiers are used in commercial office environments, in home
environments with personal computers, and in document printing and
publishing service environments. However, printing and copying
technology has not been thought of previously as a means to bridge
the gap between static printed media (i.e., paper documents), and
the "virtual world" of interactivity that includes the likes of
digital communication, networking, information provision,
advertising, entertainment and electronic commerce.
[0006] Printed media has been the primary source of communicating
information, such as newspapers and advertising information, for
centuries. The advent and ever-increasing popularity of personal
computers and personal electronic devices, such as personal digital
assistant (PDA) devices and cellular telephones (e.g., cellular
camera phones), over the past few years has expanded the concept of
printed media by making it available in an electronically readable
and searchable form and by introducing interactive multimedia
capabilities, which are unparalleled by traditional printed
media.
[0007] Unfortunately, a gap exists between the electronic
multimedia-based world that is accessible electronically and the
physical world of print media. For example, although almost
everyone in the developed world has access to printed media and to
electronic information on a daily basis, users of printed media and
of personal electronic devices do not possess the tools and
technology required to form a link between the two (i.e., for
facilitating a mixed media document).
[0008] Moreover, there are particular advantageous attributes that
conventional printed media provides such as tactile feel, no power
requirements, and permanency for organization and storage, which
are not provided with virtual or digital media. Likewise, there are
particular advantageous attributes that conventional digital media
provides such as portability (e.g., carried in storage of cell
phone or laptop) and ease of transmission (e.g., email).
[0009] One particular problem is that a publisher cannot allow
access to electronic versions of content using printed versions of
the content. For example, for the publisher of a newspaper there is
no mechanism that allows its users who receive the printed
newspaper on a daily basis to use images of the newspaper to access
the same online electronic content as well as augmented content.
Moreover, while the publisher typically has the content for the
daily newspaper in electronic form prior to printing, there
currently does not exist a mechanism to easily migrate that content
into an electronic form with augmented content.
[0010] A second problem is that there currently does not exist
mechanisms for capturing symbolic information from documents upon
printing.
SUMMARY OF THE INVENTION
[0011] The present invention overcomes the deficiencies of the
prior art with an MMR system that is particularly advantageous
because it provides an automatic mechanism for capturing symbolic
information from documents upon printing. The MMR system is also
advantageous because it has a unique architecture adapted to
respond to image queries formed of image portions or pages of a
printed publication.
[0012] In one embodiment, the MMR system comprises a plurality of
mobile devices, a computer, an MMR gateway, an MMR matching unit,
and an MMR publisher, as well as a computer with a document
authoring application, a plug-in, and a printer driver. The mobile
devices are communicatively coupled to the MMR gateway to send
retrieval requests including image queries and other contextual
information. The MMR gateway is able to couple to hundreds if not
millions of mobile computing devices and service their retrieval
requests. In one embodiment, the MMR gateway processes retrieval
requests from mobile devices and performs user authentication,
accounting, analytics and other communication and then generates an
image query that is passed on to the MMR matching unit. The MMR
matching unit includes a dispatcher, a plurality of recognition
units, and index tables as well as an image registration unit. The
MMR matching unit receives an image query from the MMR gateway and
sends it to one or more of the recognition units to identify a
result including a document, the page and the location on the page
corresponding to the image query. The image registration unit of
the MMR matching unit is also coupled to the MMR publisher to
receive new content.
[0013] The present invention also includes a number of novel
methods including a method for capturing symbolic information from
documents and for capturing printer dll functions.
[0014] The features and advantages described herein are not
all-inclusive and many additional features and advantages will be
apparent to one of ordinary skill in the art in view of the figures
and description. Moreover, it should be noted that the language
used in the specification has been principally selected for
readability and instructional purposes, and not to limit the scope
of the inventive subject matter.
BRIEF DESCRIPTION OF THE DRAWINGS
[0015] The invention is illustrated by way of example, and not by
way of limitation in the figures of the accompanying drawings in
which like reference numerals are used to refer to similar
elements.
[0016] FIG. 1 is a block diagram of one embodiment of system mixed
media reality system in accordance with the present invention.
[0017] FIG. 2A is a block diagram of a first embodiment of a mobile
device, network and MMR gateway configured in accordance with the
present invention.
[0018] FIG. 2B is a block diagram of a second embodiment of a
mobile device, network and MMR gateway configured in accordance
with the present invention.
[0019] FIGS. 2C-2H are block diagrams of various embodiments of a
mobile device plug-in, MMR gateway and MMR matching unit showing
various possible configurations in accordance with the present
invention.
[0020] FIG. 3 is a block diagram of an embodiment of an MMR gateway
in accordance with the present invention.
[0021] FIG. 4A is a block diagram of a first embodiment of a MMR
matching unit in accordance with the present invention.
[0022] FIG. 4B is a block diagram of a second embodiment of the MMR
matching unit in accordance with the present invention.
[0023] FIG. 5 is a block diagram of an embodiment of a dispatcher
in accordance with the present invention.
[0024] FIG. 6A is a block diagram of a first embodiment of an image
retrieval unit in accordance with the present invention.
[0025] FIG. 6B is a block diagram of a second embodiment of the
image retrieval unit in accordance with the present invention.
[0026] FIG. 7 is a block diagram of an embodiment of a registration
unit in accordance with the present invention.
[0027] FIG. 8 is a block diagram of an embodiment of an MMR
publisher in accordance with the present invention.
[0028] FIG. 9 is a flowchart of an embodiment of a method for
retrieving a document and location from an input image in
accordance with the present invention.
[0029] FIG. 10 is a flowchart of a method for registering an image
with the MMR matching unit in accordance with embodiments of the
present invention.
[0030] FIG. 11A illustrates a block diagram of MMR components in
accordance with one embodiment of the present invention.
[0031] FIG. 11B illustrates a set of software components included
in MMR printing software in accordance with one embodiment of the
present invention.
[0032] FIG. 12 shows an example of a fiducial mark in accordance
with one embodiment of the present invention.
[0033] FIG. 13 is a flowchart showing a method of capturing
symbolic information about a document in accordance with one
embodiment of the present invention.
[0034] FIG. 14A shows an original HTML page is shown, FIG. 14B
shows the same HTML after the fiducial marks have been added, and
FIG. 14C shows a raster image of the page.
[0035] FIG. 15 shows an example of a symbolic hotspot description
in accordance with one embodiment of the present invention.
[0036] FIGS. 16A-16E illustrate an example of a page_desc.xml for
the HTML file of FIG. 14A.
[0037] FIG. 17 shows an example of a hotspot.xml file in accordance
with one embodiment of the present invention.
[0038] FIG. 18 shows interaction of the GDI with the printer driver
when a document is printed in accordance with one embodiment of the
present invention.
[0039] FIG. 19 shows a flowchart of the process used by a print
capture dynamically linked library in accordance with one
embodiment of the present invention.
DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS
[0040] An architecture for a mixed media reality (MMR) system 100
capable of receiving the query images and returning document pages
and location as well as receiving images, hot spots and other data
and adding such information to the MMR system is described. In the
following description, for purposes of explanation, numerous
specific details are set forth in order to provide a thorough
understanding of the invention. It will be apparent, however, to
one skilled in the art that the invention can be practiced without
these specific details. In other instances, structures and devices
are shown in block diagram form in order to avoid obscuring the
invention. For example, the present invention is described in one
embodiment below with reference to use with a conventional mass
media publisher, in particular a newspaper publisher. However, the
present invention applies to any type of computing system and data
processing in which multiple types of media including electronic
media and print media are used.
[0041] Reference in the specification to "one embodiment" or "an
embodiment" means that a particular feature, structure, or
characteristic described in connection with the embodiment is
included in at least one embodiment of the invention. The
appearances of the phrase "in one embodiment" in various places in
the specification are not necessarily all referring to the same
embodiment. In particular the present invention is described below
in the context of two distinct architectures and some of the
components are operable in both architectures while others are
not.
[0042] Some portions of the detailed descriptions that follow are
presented in terms of algorithms and symbolic representations of
operations on data bits within a computer memory. These algorithmic
descriptions and representations are the means used by those
skilled in the data processing arts to most effectively convey the
substance of their work to others skilled in the art. An algorithm
is here, and generally, conceived to be a self consistent sequence
of steps leading to a desired result. The steps are those requiring
physical manipulations of physical quantities. Usually, though not
necessarily, these quantities take the form of electrical or
magnetic signals capable of being stored, transferred, combined,
compared, and otherwise manipulated. It has proven convenient at
times, principally for reasons of common usage, to refer to these
signals as bits, values, elements, symbols, characters, terms,
numbers or the like.
[0043] It should be borne in mind, however, that all of these and
similar terms are to be associated with the appropriate physical
quantities and are merely convenient labels applied to these
quantities. Unless specifically stated otherwise as apparent from
the following discussion, it is appreciated that throughout the
description, discussions utilizing terms such as "processing" or
"computing" or "calculating" or "determining" or "displaying" or
the like, refer to the action and processes of a computer system,
or similar electronic computing device, that manipulates and
transforms data represented as physical (electronic) quantities
within the computer system's registers and memories into other data
similarly represented as physical quantities within the computer
system memories or registers or other such information storage,
transmission or display devices.
[0044] The present invention also relates to an apparatus for
performing the operations herein. This apparatus may be specially
constructed for the required purposes, or it may comprise a
general-purpose computer selectively activated or reconfigured by a
computer program stored in the computer. Such a computer program
may be stored in a computer readable storage medium, such as, but
is not limited to, any type of disk including floppy disks, optical
disks, CD-ROMs, and magnetic-optical disks, read-only memories
(ROMs), random access memories (RAMs), EPROMs, EEPROMs, magnetic or
optical cards, or any type of media suitable for storing electronic
instructions, each coupled to a computer system bus.
[0045] Finally, the algorithms and displays presented herein are
not inherently related to any particular computer or other
apparatus. Various general-purpose systems may be used with
programs in accordance with the teachings herein, or it may prove
convenient to construct more specialized apparatuses to perform the
required method steps. The required structure for a variety of
these systems will appear from the description below. In addition,
the present invention is described without reference to any
particular programming language. It will be appreciated that a
variety of programming languages may be used to implement the
teachings of the invention as described herein.
System Overview
[0046] FIG. 1 shows an embodiment of a MMR system 100 in accordance
with the present invention. The MMR system 100 comprises a
plurality of mobile devices 102a-102n, an MMR gateway 104, an MMR
matching unit 106, an MMR publisher 108, and a computer 110. The
present invention provides an MMR system 100 for use in publishing,
e.g., of newspapers, magazines, books, or other publications. The
MMR system 100 is particularly advantageous because it provides an
automatic mechanism for capturing symbolic information from
documents upon printing. The MMR system 100 is also advantageous
because it has a unique architecture adapted to respond to image
queries formed of image portions or pages of a printed
publication.
[0047] The mobile devices 102a-102n are communicatively coupled by
signal lines 132a-132n, respectively, to the MMR gateway 104 to
send a "retrieval request." A retrieval request includes one or
more of "image queries," other contextual information, and
metadata. In one embodiment, an image query is an image in any
format, or one or more features of an image. Examples of image
queries include still images, video frames, and sequences of video
frames. The mobile devices 102a-102n are mobile phones including a
camera to capture images. It should be understood that the MMR
system 100 will be utilized by hundreds or even millions of users
that receive a traditional publication such as a daily newspaper.
Thus, even though only two mobile devices 102a, 102n are shown,
those skilled in the art will appreciate that the MMR gateway 104
may be simultaneously coupled to, receive and respond to retrieval
requests from numerous mobile devices 102a-102n. Alternate
embodiments for the mobile devices 102a-102n are described in more
detail below with reference to FIGS. 2A and 2B.
[0048] As noted above, the MMR gateway 104 is able to couple to
hundreds if not millions of mobile computing devices 102a-102n and
service their retrieval requests. The MMR gateway 104 also is
communicatively coupled to the computer 110 by signal line 130 for
administration and maintenance of the MMR gateway 104 and running
business applications. In one embodiment, the MMR gateway 104
creates and presents a web portal for access by the computer 110 to
run business applications as well as access logs of use of the MMR
system 100. The computer 110 can be any conventional computing
device such as a personal computer, including a processor and other
standard components known in the art. The main function of the MMR
gateway 104 is processing retrieval requests from the mobile
devices 102a-102n and returning recognition results back to the
mobile devices 102a-102n. In one embodiment, the recognition
results include one or more of a Boolean value (true/false) and if
true, a page ID and a location on the page. In other embodiments,
the recognition results also include one or more from the group of
actions, a message acknowledging that the recognition was
successful (or not), and consequences of that decision, such as the
sending of an email message, a document, actions defined within a
portable document file, addresses such as URLs, binary data such as
video, information capable of being rendered on the mobile device
102, menus with additional actions, raster images, image features,
etc. The MMR gateway 104 processes received retrieval requests by
performing user authentication, accounting, analytics, and other
communication. The MMR gateway 104 also generates image query and
recognition parameters from the retrieval request, and passes them
on to the MMR matching unit 106 via signal line 134. Embodiments
and operation of the MMR gateway 104 are described in greater
detail below with reference to FIG. 3.
[0049] The MMR matching unit 106 receives the image query from the
MMR gateway 104 on signal line 134 and sends it to one or more of
recognition units to identify a result including a document, page,
and location on the page corresponding to the image query, referred
to generally throughout this application as the "retrieval
process." The result is returned from the MMR matching unit 106 to
the MMR gateway 104 on signal line 134. In addition to the result,
the MMR matching unit 106 may also return other related information
such as hotspot data, including advertising content. The MMR
matching unit 106 also includes components for receiving new
content and updating and reorganizing index tables used in the
retrieval process. The process of adding new content to the MMR
matching unit 106 is referred to generally throughout this
application as the "registration process." In one embodiment, the
MMR matching unit 106 is coupled to the output of the MMR publisher
108 via signal lines 138 and 140 to provide new content used to
update index tables of the MMR matching unit 106. In alternate
embodiment, the MMR publisher 108 is coupled to the MMR gateway 104
by signal line 138 and the MMR gateway 104 is in turn coupled by
signal line 136 to the MMR matching unit 106. In this alternate
environment, MMR gateway 104 extracts augmented data such as
hotspot information, stores it and passes the images, page
references and other information to the MMR matching unit 106 for
updating of the index tables. Various embodiments of the MMR
matching unit 106 and its components are described in more detail
below with reference to FIG. 4A-7.
[0050] The MMR publisher 108 includes a conventional publishing
system used to generate newspapers or other types of periodicals.
In one embodiment, the MMR publisher 108 also includes components
for generating additional information needed to register images of
printed documents with the MMR system 100. The information provided
by the MMR publisher 108 to the MMR matching unit 106 includes an
image file, bounding box data, hotspot data, and a unique page
identification number. In one exemplary embodiment, this is a
document in portable document format by Adobe Corp. of San Jose,
Calif. and bounding box information. The publisher 108 also may
provide information about the hierarchical structure associated
with a publication, e.g., what documents are in the collection,
what pages are in each document, and what zones are on each page,
as well as a neighborhood preference function for pages and/or
documents for publications typically read in a specific order. An
embodiment for the MMR publisher 108 is described in more detail
below with reference to FIG. 8.
Mobile Device 102
[0051] Referring now to FIGS. 2A and 2B, the first and second
embodiment for the mobile device 102 will be described.
[0052] FIG. 2A shows a first embodiment of the coupling 132 between
the mobile device 102 and the MMR gateway 104. In this embodiment,
the mobile device 102 is any mobile phone (or other portable
computing device with communication capability) that includes a
camera. For example, the mobile device 102 may be a smart phone
such as the Blackberry.RTM. manufactured and sold by Research In
Motion. The mobile device 102 is adapted for wireless communication
with the network 202 by a communication channel 230. The network
202 is a conventional type such as a cellular network maintained by
wireless carrier and may include a server. In this embodiment, the
mobile device 102 captures an image and sends the image to the
network 202 over communications channel 230 such as by using a
multimedia messaging service (MMS). The network 202 can also use
the communication channel 230 to return results such as using MMS
or using a short message service (SMS). As illustrated, the network
202 is in turn coupled to the MMR gateway 104 by signal lines 232.
Signal lines 232 represent a channel for sending MMS or SMS
messages as well as a channel for receiving hypertext transfer
protocol (HTTP) requests and sending HTTP responses. Those skilled
in the art will recognize that this is just one example of the
coupling between the mobile device 102 and the MMR gateway 104. In
an alternate embodiment for example, Bluetooth.RTM., WiFi or any
other wireless communication protocol may be used as part of
communication coupling between the mobile device 102 and the MMR
gateway 104. The mobile device 102 and the MMR gateway 104 could be
coupled in any other ways understood by those skilled in the art
(e.g., direct data connection, SMS, WAP, email) so long as the
mobile device 102 is able to transmit images to the MMR gateway 104
and the MMR gateway 104 is able to respond by sending document
identification, page number and location information.
[0053] Referring now to FIG. 2B, a second embodiment of the mobile
device 102 is shown. In this second embodiment, the mobile device
102 is a smart phone such as the iPhone.TM. manufactured and sold
by Apple Computer Inc. of Cupertino Calif. The second embodiment
has a number of components similar to those of the first
embodiment, and therefore, like reference numbers are used to
reference like components with the same or similar functionality.
Notable differences between the first embodiment and the second
embodiment include a quality predictor plug-in 204 that is
installed on the mobile device 102, and a Web server 206 coupled by
signal line 234 to the network 202. The quality predictor plug-in
204 analyzes the images captured by the mobile device 102. The
quality predictor plug-in 204 provides additional information
produced by its analysis and includes that information as part of
the retrieval request sent to the MMR gateway 104 to improve the
accuracy of recognition. In an alternate embodiment, the output of
the quality predictor plug-in 204 is used to select which images
are transmitted from the mobile device 102 to the MMR gateway 104.
For example, only those images that have a predicted quality above
a predetermined threshold (e.g., images capable of being
recognized) are transmitted from the mobile device 102 to the MMR
gateway 104. Since transmission of images requires significant
bandwidth and the communication channel 230 between the mobile
device 102 and the network 202 may have limited bandwidth, using
the quality predictor plug-in 204 to select which images to
transmit is particularly advantageous. The second embodiment shown
in FIG. 2B also illustrates how the results returned from the MMR
gateway 104 or other information provided by the quality predictor
plug-in 204 can be used by the mobile device 102 to access hotspot
or augmented information available on a web server 206. In such a
case, the results from the MMR gateway 104 or output of the quality
predictor plug-in 204 would include information that can be used to
access Web server 206 such as with a conventional HTTP request and
using web access capabilities of the mobile device 102.
[0054] It should be noted that regardless of whether the first
embodiment or the second embodiment of the mobile device 102 is
used, the mobile device 102 generates the retrieval request that
includes: a query image, a user or device ID, a command and other
contact information such as device type, software, plug-ins,
location (for example if the mobile device includes a GPS
capability), device and status information (e.g., device model,
macro lens on/off status, autofocus on/off, vibration on/off, tilt
angle, etc), context-related information (weather at the phone's
location, time, date, applications currently running on the phone),
user-related information (e.g., id number, preferences, user
subscriptions, user groups and social structures, action and
action-related meta data such as email actions and emails waiting
to be sent), etc.
[0055] Referring now to FIGS. 2C-2H, various embodiments are shown
of a plug-in (client 250) for the mobile device 102, the MMR
gateway 104 and MMR matching unit 106 represented generally as
including a server 252 that has various possible configurations in
accordance with the present invention. More particularly, FIGS.
2C-2H illustrate how the components of the plug-in or client 250
can have varying levels of functionality and the server 252 can
also have varying levels of functionality that parallel or match
with the functionality of the client 250. In the various
embodiments of FIGS. 2C-2H, either the client 250 or the server 252
includes: an MMR database 254; a capture module 260 for capturing
an image or video; a preprocessing module 262 for processing the
image before feature extraction for improved recognition such as
quality prediction; a feature extraction module 264 for extracting
image features; a retrieval module 266 for using features to
retrieve information from the MMR database 254; a send message
module 268 for sending messages from the server 252 to the client
250; an action module 270 for performing an action; a preprocessing
and prediction module 272 for processing the image prior to feature
extraction; a feedback module 274 for presenting information to the
user and receiving input; a sending module 276 for sending
information from the client 250 to the server 252; and a streaming
module 278 for streaming video from the client 250 to the server
252.
[0056] FIG. 2C illustrates one embodiment for the client 250 and
the server 252 in which the client 250 sends an image or video
and/or metadata to the server 252 for processing. In this
embodiment, the client 250 includes the capture module 260. The
server 252 includes: the MMR database 254, the preprocessing module
262, the feature extraction module 264, the retrieval module 266,
the send message module 268 and the action module 270.
[0057] FIG. 2D illustrates another embodiment for the client 250
and the server 252 in which the client 250 captures an image or
video, runs quality prediction, and sends an image or video and/or
metadata to the server 252 for processing. In this embodiment, the
client 250 includes: the capture module 260, the preprocessing and
prediction module 272, the feedback module 274 and the sending
module 276. The server 252 includes: the MMR database 254, the
preprocessing module 262, the feature extraction module 264, the
retrieval module 266, the send message module 268 and the action
module 270. It should be noted that in this embodiment the image
sent to the server 252 may be different than the captured image.
For example, it may be digitally enhanced, sharpened, or may be
just binary data.
[0058] FIG. 2E illustrates another embodiment for the client 250
and the server 252 in which the client 250 captures an image or
video, performs feature extraction and sends image features to the
server 252 for processing. In this embodiment, the client 250
includes: the capture module 260, the feature extraction module
264, the preprocessing and prediction module 272, the feedback
module 274 and the sending module 276. The server 252 includes: the
MMR database 254, the retrieval module 266, the send message module
268 and the action module 270. It should be noted that in this
embodiment feature extraction may include preprocessing. After
features are extracted, the preprocessing and prediction module 272
may run on these features and if the quality of the features is not
satisfactory, the user may be asked to capture another image.
[0059] FIG. 2F illustrates another embodiment for the client 250
and the server 252 in which the entire retrieval process is
performed at the client 250. In this embodiment, the client 250
includes: the capture module 260, the feature extraction module
264, the preprocessing and prediction module 272, the feedback
module 274 and the sending module 276, the MMR database 254, and
the retrieval module 266. The server 252 need only have the action
module 270.
[0060] FIG. 2G illustrates another embodiment for the client 250
and the server 252 in which the client 250 streams video to the
server 252. In this embodiment, the client 250 includes the capture
module 260 and a streaming module 278. The server 252 includes the
MMR database 254, the preprocessing module 262, the feature
extraction module 264, the retrieval module 266, the send message
module 268 and the action module 270. Although not shown, the
client 250 can run a predictor in the captured video stream and
provide user feedback on where to point the camera or how to
capture better video for retrieval. In a modification of this
embodiment, the server 252 streams back information related to the
captured video and the client 250 can overlay that information on a
video preview screen.
[0061] FIG. 2H illustrates another embodiment for the client 250
and the server 252 in which the client 250 runs a recognizer and
the server 252 streams MMR database information to a local database
operable with the client 250 based upon a first recognition result.
This embodiment is similar to that described above with reference
to FIG. 2F. For example, the entire retrieval process for one
recognition algorithm is run at the client 250. If the recognition
algorithm fails, the query is handed to the server 252 for running
more complex retrieval algorithm. In this embodiment, the client
250 includes: the capture module 260, the feature extraction module
264, the preprocessing and prediction module 272, the feedback
module 274, the sending module 276, the MMR database 254 (a local
version), and the retrieval module 266. The server 252 includes
another retrieval module 266, the action module 270 and the MMR
database 254 (a complete and more complex version). In one
embodiment, if the query image cannot be recognized with the local
MMR database 254, the client 250 sends an image for retrieval to
the server 252 and that initiates an update of the local MMR
database 254. Alternatively, the client 250 may contain an updated
version of a database for one recognizer, but if the query image
cannot be retrieved from the local MMR database 254, then a
database for another retrieval algorithm may be streamed to the
local MMR database 254.
MMR Gateway 104
[0062] Referring now to FIG. 3, one embodiment of the MMR gateway
104 is shown. This embodiment of the MMR gateway 104 comprises a
server 302, a Web server 304, a data store 306, a portal module
308, a log 310, one or more applications 312, an authentication
module 314, an accounting module 316, a mail module 318 and an
analytics module 320.
[0063] As noted above, one of the primary functions of the MMR
gateway 104 is to communicate with many mobile devices 102 to
receive retrieval requests and send responses including a status
indicator (true=recognized/false=not recognized), a page
identification number, a location on the page and other information
such as hotspot data. A single MMR gateway 104 can respond to
hundreds or millions of retrieval requests. For convenience and
ease of understanding only a single MMR gateway 104 is shown in
FIGS. 1 and 3, however, those skilled in the art will recognize
that in other embodiments any number of MMR gateways 104 may be
utilized to service the needs of a multitude of mobile devices 102.
More particularly, the server 302 of the MMR gateway 104 is coupled
to signal lines 132 for communication with various mobile devices
102. The server 302 receives retrieval requests from the mobile
devices 102 via signal lines 132 and sends responses back to the
mobile devices 102 using the same signal lines 132. In one
embodiment, the retrieval request includes: a command, a user
identification number, an image and other context information. For
example, other context information may include: device information
such as the make, model or manufacture of the mobile device 102;
location information such as provided by a GPS system that is part
of the mobile device or by triangulation; environmental information
such as time of day, temperature, weather conditions, lighting,
shadows, object information; and placement information such as
distance, location, tilt and jitter.
[0064] The server 302 is also coupled to signal line 130 for
communication with the computer 110. Again, for convenience and
ease of understanding only a single computer 110 and signal line
130 are shown in FIGS. 1A, 1B, and 3, but any number of computing
devices may be adapted for communication with the server 302. The
server 302 facilitates communication between the computer 110 and
the portal module 308, the log module 310 and the applications 312.
The server 302 is coupled to the portal module 308, the log module
310 and the applications 312 by signal line 330. As will be
described in more detail below, the modules cooperate with the
server 302 to present a web portal that provides a user experience
for exchanging information. The Web portal 308 can also be used for
system monitoring, maintenance and administration.
[0065] The server 302 processes the retrieval request and generates
an image query and recognition parameters that are sent via signal
line 134 to the MMR matching unit 106 for recognition. The server
302 also receives recognition responses from the MMR matching unit
106 via signal line 134. The server 302 also processes the
retrieval request and sends information via signal line 330 to the
other components of the MMR gateway 104 as will be described below.
The server 302 is also adapted for communication with the MMR
publisher 108 by signal line 138 and the MMR matching unit 106 via
signal line 136. The signal line 138 provides a path for the MMR
publisher 108 to send Web content for hotspots to the Web server
304 and to provide other information to the server 302. In one
embodiment, the server 302 receives information from the MMR
publisher 108 and sends that information via signal line 136 for
registration with the MMR matching unit 106.
[0066] The web server 304 is a conventional type and is responsible
for accepting requests from clients and sending responses along
with data contents, such as web pages, documents and linked objects
(images, etc.) The Web server 304 is coupled to data store 306 such
as a conventional database. The Web server 304 is adapted for
communication via signal line 234 to receive HTTP requests from any
communication device across a network such as the Internet. The Web
server 304 is also coupled to signal line 138 as described above to
receive Web content associated with hotspots for storage in the
data store 306 and then for later retrieval and transmission in
response to HTTP requests. Those skilled in the art will understand
that inclusion of the Web server 304 and data store 306 as part of
the MMR gateway 104 is merely one embodiment and that the Web
server 304 and the data store 306 may be operational in any number
of alternate locations or configuration so long as the Web server
304 is accessible to mobile devices 102 and computers 110 via the
Internet.
[0067] In one embodiment, the portal module 308 is software or
routines operational on the server 302 for creation and
presentation of the Web portal. The portal module 308 is coupled to
signal line 330 for communication with the server 302. In one
embodiment, the web portal provides an access point for
functionality including administration and maintenance of other
components of the MMR gateway 104. In another embodiment, the web
portal provides an area where users can share experiences related
to MMR documents. In yet another embodiment, the web portal is an
area where users can access business applications and the log 310
of usage.
[0068] The log 310 is a memory or storage area for storing a list
of the retrieval requests received by the server 302 from mobile
devices 102 and all corresponding responses sent by the server 302
to the mobile devices. In another embodiment, the log 310 also
stores a list of the image queries generated and sent to the MMR
matching unit 106 and the recognition responses received from the
MMR matching unit 106. The log 310 is coupled to signal line 330
for access by the server 302.
[0069] The one or more business applications 312 are software and
routines for providing functionality related to the processing of
MMR documents. In one embodiment the one or more business
applications 312 are executable on the server 302. The business
applications 312 can be any one of a variety of types of business
applications adapted to utilize information related to the
processing of retrieval quests and delivery of recognition
responses such as but not limited to accounting, groupware,
customer relationship management, human resources, outsourcing,
loan origination, customer care, service relationships, etc.
[0070] The authentication module 314 is software and routines for
maintaining a list of authorized users and granting access to the
MMR system 110. In one embodiment, the authentication module 314
maintains a list of user IDs and passwords corresponding to
individuals who have created an account in the system 100, and
therefore, are authorized to use MMR gateway 104 and the MMR
matching unit 106 to process retrieval requests. The authentication
module 314 is communicatively coupled by signal line 330 to the
server 302. But as the server 302 receives retrieval requests they
can be processed and compared against information in the
authentication module 314 before generating and sending the
corresponding image query on signal line 134. In one embodiment,
the authentication module 314 also generates messages for the
server 302 to return to the mobile device 102 instances when the
mobile device is not authorized, the mobile device has not
established an account, or the account for the mobile device 102 is
locked such as due to abuse or lack of payment.
[0071] The accounting module 316 is software and routines for
performing accounting related to user accounts and use of the MMR
system 100. In one embodiment, the retrieval services are provided
under a variety of different economic models such as but not
limited to use of the MMR system 100 under a subscription model, a
charge per retrieval request model or various other pricing models.
In one embodiment, the MMR system 100 provides a variety of
different pricing models and is similar to those currently offered
for cell phones and data networks. The accounting module 316 is
coupled to the server 302 by signal line 330 to receive an
indication of any retrieval request received by the server 302. In
one embodiment, the accounting module 316 maintains a record of
transactions (retrieval request/recognition responses) processed by
the server 302 for each mobile device 102. Although not shown, the
accounting module 316 can be coupled to a traditional billing
system for the generation of an electronic or paper bill.
[0072] The mail module 318 is software and routines for generating
e-mail and other types of communication. The mail module 318 is
coupled by signal at 330 to the server 302. In one embodiment, the
mobile device 102 can issue retrieval requests that include a
command to deliver a document or a portion of a document or other
information via e-mail, facsimile or other traditional electronic
communication means. The mail module 318 is adapted to generate and
send such information from the MMR gateway 104 to an addressee as
prescribed by the user. In one embodiment, each user profile has
associated addressees which are potential recipients of information
retrieved.
[0073] The analytics module 320 is software and routines for
measuring the behavior of users of the MMR system 100 according to
one embodiment. The analytics module 320 is also software and
routines for measuring the effectiveness and accuracy of feature
extractors and recognition performed by the MMR matching unit 106.
The analytics module 320 measures use of the MMR system 100
including which images are most frequently included as part of
retrieval requests, which hotspot data is most often accessed, the
order in which images are retrieved, the first image in the
retrieval process, and other key performance indicators used to
improve the MMR experience and/or a marketing campaign's audience
response. In one embodiment, the analytics module 320 measures
metrics of the MMR system 100 and analyzes the metrics used to
measure the effectiveness of hotspots and hotspot data. The
analytics module 320 is coupled to the server 302, the
authentication module 314 and the accounting module 316 by signal
line 330. The analytics module 320 is also coupled by the server
302 to signal line 134 and thus can access the components of the
MMR matching unit 106 to retrieve recognition parameters, images
features, quality recognition scores and any other information
generated or used by the MMR matching unit 106. The analytics
module 320 can also perform a variety of data retrieval and
segmentation based upon parameters or criteria of users, mobile
devices 102, page IDs, locations, etc.
[0074] In one embodiment, the MMR gateway 104 also includes a
hotspot database 404. The hotspot database 404 is shown in FIG. 3
with dashed lines to reflect that inclusion in the MMR gateway 104
is an alternate embodiment. The hotspot database 404 is coupled by
signal line 436 to receive the recognition responses via line 134.
The hotspot database 404 uses these recognition responses to query
the database and output via line 432 the hotspot content, e.g.,
such as advertisements, corresponding to the recognition responses.
This hotspot content is sent to the server 302 so that it can be
included with the recognition responses and sent to the requesting
mobile device 102.
MMR Matching Unit 106
[0075] Referring now to FIGS. 4A and 4B, two embodiments for the
MMR matching unit 106 will be described. The basic function of the
MMR matching unit 106 is to receive an image query, send the image
query for recognition, perform recognition on the images in the
image query, retrieve hotspot information, combine the recognition
result with hotspot information and send it back to the MMR gateway
104.
[0076] FIG. 4A illustrates a first embodiment of the MMR matching
unit 106. The first embodiment of the MMR matching unit 106
comprises a dispatcher 402, a hotspot database 404, an acquisition
unit 406, an image registration unit 408, and a dynamic load
balancer 418. The acquisition unit 406 further comprises a
plurality of the recognition units 410a-410n and a plurality of
index tables 412a-412n. The image registration unit 408 further
comprises an indexing unit 414 and a master index table 416.
[0077] The dispatcher 402 is coupled to signal line 134 for
receiving an image query from and sending recognition results to
the MMR gateway 104. The dispatcher 402 is responsible for
assigning and sending an image query to respective recognition
units 410a-410n. In one embodiment, the dispatcher 402 receives an
image query, generates a recognition unit identification number and
sends the recognition unit identification number and the image
query to the acquisition unit 406 for further processing. The
dispatcher 402 is coupled to signal line 430 to send the
recognition unit identification number and the image query to the
recognition units 410a-410n. The dispatcher 402 also receives the
recognition results from the acquisition unit 406 via signal line
430. The dispatcher 402 also retrieves hotspot content from hotspot
database 404 corresponding to the recognition results. One
embodiment for the dispatcher 402 will be described in more detail
below with reference to FIG. 5.
[0078] An alternate embodiment for the hotspot database 404 has
been described above with reference to FIG. 3 where the hotspot
database is part of the MMR gateway 104. However, the preferred
embodiment for the hotspot database 404 is part of the MMR matching
unit 106 as shown in FIG. 4A. Regardless of the embodiment, the
hotspot database 404 has a similar functionality. The hotspot
database 404 is used to store hotspot information, such as links,
link preference information, and neighbor preference information
for pages and documents. Once an image query has been recognized
and recognition results are produced, these recognition results are
used as part of a query of the hotspot database 404 to retrieve
hotspot information associated with the recognition results. The
retrieved hotspot information is then output on signal line 134 to
the MMR gateway 104 for packaging and delivery to the mobile device
102. As shown in FIG. 4A, the hotspot database 404 is coupled to
the dispatcher 402 by signal line 436 to receive queries including
recognition results. The hotspot database 404 is also coupled by
signal line 432 and signal line 134 to the MMR gateway 104 for
delivery of query results. The hotspot database 404 is also coupled
to signal line 136 to receive new hotspot information for storage
from the MMR publisher 108.
[0079] Referring again to FIG. 4A, the acquisition unit 406
comprises the plurality of the recognition units 410a-410n and a
plurality of index tables 412a-412n. Each of the recognition units
410a-410n has and is coupled to a corresponding index table
412a-412n. In one embodiment, each recognition unit 410/index table
412 pair is on the same server. The dispatcher 402 sends the image
query to one or more recognition units 410a-410n. In one embodiment
that includes redundancy, the image query is sent from the
dispatcher 402 to a plurality of recognition units 410 for
recognition and retrieval and the index tables 412a-n index the
same data. In the serial embodiment, the image query is sent from
the dispatcher 402 to a first recognition unit 410a. If recognition
is not successful on the first recognition unit 410a, the image
query is passed on to a second recognition unit 410b, and so on. In
yet another embodiment, the dispatcher 402 performs some
preliminary analysis of the image query and then selects a
recognition unit 410a-410n best adapted and most likely to be
successful at recognizing the image query. In another embodiment,
one or more of the recognition unit 410 index table 412 pairs
include a segmented page index, which includes a segmented version
of ever object in the master index table 416, wherein the
segmentation defines polygon-shaped zones on a page.
[0080] Those skilled in the art will understand that there are a
variety of configurations for the plurality of recognition units
410a-410n and the plurality of index tables 412a-412n. Example
embodiments for the acquisition unit 406 will be described in more
detail below with reference to FIGS. 6A and 6B. It should be
understood that the index tables 412a-412n can be updated at
various times as depicted by the dashed lines 434 from the master
index table 416.
[0081] The image registration unit 408 comprises the indexing unit
414 and the master index table 416. The image registration unit 408
has an input coupled to signal on 136 to receive updated
information from the MMR publisher 108 and broker 112 and an input
coupled to signal line 438 to receive updated information from the
dynamic load balancer 418. The image registration unit 408 is
responsible for maintaining the master index table 416 and
migrating all or portions of the master index table 416 to the
index tables 412a-412n (slave tables) of the acquisition unit 406.
In one embodiment, the indexing unit 414 receives images, unique
page IDs, and other information, and converts it into index table
information that is stored in the master index table 416. The
indexing unit 414 also cooperates with the MMR publisher 108 to
maintain a unique page identification numbering system that is
consistent across image pages generated by the MMR publisher 108,
the image pages stored in the master index table 416, and the page
numbers used in referencing data in the hotspot database 404.
[0082] One embodiment for the image registration unit 408 is shown
and described in more detail below with reference to FIG. 7.
[0083] The dynamic load balancer 418 has an input coupled to signal
line 430 to receive the query image from the dispatcher 402 and the
corresponding recognition results from the acquisition unit 406.
The output of the dynamic load balancer 418 is coupled by signal
line 438 to an input of the image registration unit 408. The
dynamic load balancer 418 provides input to the image registration
unit 408 that is used to dynamically adjust the index tables
412a-412n of the acquisition unit 406. In particular, the dynamic
load balancer 418 monitors and evaluates the image queries that are
sent from the dispatcher 402 to the acquisition unit 406 for a
given period of time. Based on the usage, the dynamic load balancer
418 provides input to adjust the index tables 412a-412n. For
example, the dynamic load balancer 418 may measure the image
queries for a day. Based on the measured usage for that day, the
index tables are modified and configured in the acquisition unit
406 to match the usage measured by the dynamic load balancer
418.
[0084] FIG. 4B illustrates a second embodiment of the MMR matching
unit 106. In the second embodiment, many of the components of the
MMR matching unit 106 have the same or a similar function to
corresponding elements of the first embodiment. Thus, like
reference numbers have been used to refer to like components with
the same or similar functionality. The second embodiment of the MMR
matching unit 106 includes the dispatcher 402, the hotspot database
404, and the dynamic load balancer 418 similar to the first
embodiment of the MMR matching unit 106. However, the acquisition
unit 406 and the image registration unit 408 are different than
that described above with reference to FIG. 4A. In particular, the
acquisition unit 406 and the image registration unit 408 utilize a
shared SQL database for the index tables and the master table. More
specifically, there is the master index table 416 and a mirrored
database 418 that includes the local index tables 412a-n. Moreover,
a conventional functionality of SQL database replication is used to
generate the mirror images of the master index table 416 stored in
the index tables 412a-n for use in recognition. The image
registration unit 408 is configured so that when new images are
added to the master index table 416 they are immediately available
to all the recognition units 410. This is done by mirroring the
master index table 416 across all the local index tables 412a-n
using large RAM (not shown) and database mirroring technology.
Dispatcher 402
[0085] Referring now to FIG. 5, an embodiment of the dispatcher 402
shown. The dispatcher 402 comprises a quality predictor 502, an
image feature order unit 504, and a distributor 506. The quality
predictor 502, the image feature order unit 504, and the
distributor 506 are coupled to signal line 532 to receive image
queries from the MMR gateway 104. The distributor 506 is also
coupled to receive the output of the quality predictor 502 and the
image feature order unit 504. The distributor 506 includes a FIFO
queue 508 and a controller 510. The distributor 506 generates an
output on signal line 534 that includes the image query and a
recognition unit identification number (RUID). Those skilled in the
art will understand that in other embodiments the image query may
be directed to any particular recognition unit using a variety of
means other than the RUID. As image queries are received on the
signal line 532, the distributor 506 receives the image queries and
places them in the order in which they are received into the FIFO
queue 508. The controller 510 receives a recognizability score for
each image query from the quality predictor 502 and also receives
an ordering signal from the image feature order unit 504. Using
this information from the quality predictor 502 and the image
feature order unit 504, the controller 510 selects image queries
from the FIFO queue 508, assigns them to particular recognition
units 410 and sends the image query to the assigned recognition
unit 410 for processing. The controller 510 maintains a list of
image queries assigned to each recognition unit 410 and the
expected time to completion for each image (as predicted by the
image feature order unit 504). The total expected time to empty the
queue for each recognition unit 410 is the sum of the expected
times for the images assigned to it. The controller 510 can execute
several queue management strategies. In a simple assignment
strategy, image queries are removed from the FIFO queue 508 in the
order they arrived and assigned to the first available recognition
unit 410. In a balanced response strategy, the total expected
response time to each query is maintained at a uniform level and
query images are removed from the FIFO queue 508 in the order they
arrived, and assigned to the FIFO queue 508 for a recognition unit
so that its total expected response time is as close as possible to
the other recognition units. In an easy-first strategy, images are
removed from the FIFO queue 508 in an order determined by their
expected completion times--images with the smallest expected
completion times are assigned to the first available recognition
unit. In this way, users are rewarded with faster response time
when they submit an image that's easy to recognize. This could
incentivize users to carefully select the images they submit. Other
queue management strategies are possible.
[0086] The dispatcher 402 also receives the recognition results
from the recognition units 410 on signal line 530. The recognition
results include a Boolean value (true/false) and if true, a page ID
and a location on the page. In one embodiment, the dispatcher 402
merely receives and retransmits the data to the MMR gateway
104.
[0087] Referring again to FIG. 5, the quality predictor 502
receives image queries and generates a recognizability score used
by the dispatcher 402 to route the image query to one of the
plurality of recognition units 410. In one embodiment, the quality
predictor 502 also receives as inputs context information and
device parameters. In one embodiment, the recognizability score
includes information specifying the type of recognition algorithm
most likely to produce a valid recognition result.
[0088] The image feature order unit 504 receives image queries and
outputs an ordering signal. The image feature order unit 504
analyzes an input image query and predicts the time required to
recognize an image by analyzing the image features it contains. The
difference between the actual recognition time and the predicted
time is used to adjust future predictions thereby improving
accuracy. In the simplest of embodiments, simple images with few
features are assigned to lightly loaded recognition units 410 so
that they will be recognized quickly and the user will see the
answer immediately. In one embodiment, the features used by the
image order feature unit 504 to predict the time are different than
the features used by recognition units 410 for actual recognition.
For example, the number of corners detected in an image is used to
predict the time required to analyze the image. The feature set
used for prediction need only be correlated with the actual
recognition time. In one embodiment, several different features
sets are used and the correlations to recognition time measured
over some period. Eventually, the feature set that is the best
predictor and lowest cost (most efficient) would be determined and
the other feature sets could be discarded.
Acquisition Unit 406
[0089] Referring now to FIGS. 6A and 6B, embodiments of the
acquisition unit 406 will be described.
[0090] FIG. 6A illustrates one embodiment for the acquisition unit
406 where the recognition unit 410 and index table 412 pairs are
partitioned based on the content or images that they index. This
configuration is particularly advantageous for mass media
publishers that provide content on a periodic basis. The
organization of the content in the index tables 412 can be
partitioned such that the content most likely to be accessed will
be available on the greatest number of recognition unit 410 and
index table 412 pairs. Those skilled in the art will recognize that
the partition described below is merely one example and that
various other partitions based on actual usage statistics measured
over time can be employed. As shown in FIG. 6A, the acquisition
unit 406 comprises a plurality of recognition units 410a-h and a
plurality of index tables 412a-h. The plurality of recognition
units 410a-h is coupled to signal line 430 to receive image queries
from the dispatcher 402. Each of the plurality of recognition units
410a-h is coupled to a corresponding index table 412a-h. The
recognition units 410 extract features from the image query and
compare those image features to the features stored in the index
table to identify a matching page and location on that page.
Example recognition and retrieval systems and methods are disclosed
in U.S. patent application Ser. No. 11/461,017, titled "System And
Methods For Creation And Use Of A Mixed Media Environment," filed
Jul. 31, 2006, attorney docket no. 20412-11713; U.S. patent
application Ser. No. 11/461,279, titled "Method And System For
Image Matching In A Mixed Media Environment," filed Jul. 31, 2006,
attorney docket no. 20412-11714; U.S. patent application Ser. No.
11/461,286, titled "Method And System For Document Fingerprinting
Matching In A Mixed Media Environment," filed Jul. 31, 2006,
attorney docket no. 20412-11715; U.S. patent application Ser. No.
11/461,294, titled "Method And System For Position-Based Image
Matching In A Mixed Media Environment," filed Jul. 31, 2006,
attorney docket no. 20412-11716; U.S. patent application Ser. No.
11/461,300, titled "Method And System For Multi-Tier Image Matching
In A Mixed Media Environment," filed Jul. 31, 2006, attorney docket
no. 20412-11717; U.S. patent application Ser. No. 11/461,147,
titled "Data Organization and Access for Mixed Media Document
System," filed Jul. 31, 2006, attorney docket no. 20412-11730; U.S.
patent application Ser. No. 11/461,164, titled "Database for Mixed
Media Document System," filed Jul. 31, 2006, attorney docket no.
20412-11731; U.S. patent application Ser. No. 11/461,109, titled
"Searching Media Content For Objects Specified Using Identifiers,"
filed Jul. 31, 2006, attorney docket no. 20412-11735; U.S. patent
application Ser. No. 12/059,583, titled "Invisible Junction Feature
Recognition For Document Security Or Annotation," filed Mar. 31,
2008, attorney docket no. 20412-13397; U.S. patent application Ser.
No. 12/121,275, titled "Web-Based Content Detection In Images,
Extraction And Recognition," filed May 15, 2008, attorney docket
no. 20412-14041; U.S. patent application Ser. No. 11/776,510,
titled "Invisible Junction Features For Patch Recognition," filed
Jul. 11, 2007, attorney docket no. 20412-12829; U.S. patent
application Ser. No. 11/776,520, titled "Information Retrieval
Using Invisible Junctions and Geometric Constraints," filed Jul.
11, 2007, attorney docket no. 20412-13136; U.S. patent application
Ser. No. 11/776,530, titled "Recognition And Tracking Using
Invisible Junctions," filed Jul. 11, 2007, attorney docket no.
20412-13137; and U.S. patent application Ser. No. 11/777,142,
titled "Retrieving Documents By Converting Them to Synthetic Text,"
filed Jul. 12, 2007, attorney docket no. 20412-12590; and U.S.
patent application Ser. No. 11/624,466, titled "Synthetic Image and
Video Generation From Ground Truth Data," filed Jan. 18, 2007,
attorney docket no. 20412-12219; which are incorporated by
reference in their entirety.
[0091] As shown in FIG. 6A, the recognition unit 410/index table
412 pairs are grouped according to the content that in the index
tables 412. In particular, the first group 612 of recognition units
410a-d and index tables 412a-d is used to index the pages of a
publication such as a newspaper for a current day. For example,
four of the eight recognition units 410 are used to index content
from the current day's newspaper because most of the retrieval
requests are likely to be related to the newspaper that was
published in the last 24 hours. A second group 614 of recognition
units 410e-g and corresponding index tables 412e-g are used to
store pages of the newspaper from recent past days, for example the
past week. A third group 606 of recognition unit 410h and index
table 412h is used to store pages of the newspaper from older past
days, for example for the past year. This allows the organizational
structure of the acquisition unit 406 to be optimized to match the
profile of retrieval requests received. Moreover, the operation of
the acquisition unit 406 can be modified such that a given image
query is first sent to the first group 612 for recognition, and if
the first group 612 is unable to recognize the image query, it is
sent to the second group 614 for recognition and so on.
[0092] It should be noted that the use of four recognition units
410 and index tables 412 as the first group 612 is merely be by way
example and used demonstrate a relative proportion as compared with
the number of recognition units 410 and index tables 412 in the
second group 614 and the third group 616. The number of recognition
units 410 and index tables 412 in any particular group 612, 614 and
616 may be scaled the modified based on the total number of
recognition units 410 and index tables 412. Furthermore, the number
of recognition units 410 and index tables 412 in any particular
group 612, 614 and 616 may be adapted so that it matches the
profile of all users sending retrieval request to the acquisition
unit 406 for a given publication.
[0093] FIG. 6B illustrates a second embodiment for the acquisition
unit 406 where the recognition units 410 and index tables 412 are
partitioned based upon the type of recognition algorithm they
implement. In the second embodiment, the recognition units 410 are
also coupled such that the failure of a particular recognition unit
to generate a registration result causes the input image query to
be sent to another recognition unit for processing. Furthermore, in
the second embodiment, the index tables 412 include feature sets
that are varied according to different device and environmental
factors of image capture devices (e.g., blur).
[0094] The second embodiment of the acquisition unit 406 includes a
plurality of recognition units 410a-410e, a plurality of the index
tables 412a-412e and a result combiner 610. In this embodiment, the
recognition units 410a-410e each utilizes a different type of
recognition algorithm. For example, recognition units 410a, 410b
and 410c use an invisible junction algorithm; recognition unit 410d
uses a brick wall coding algorithm; and recognition unit 410e uses
a path coding algorithm for recognition and retrieval of page
numbers and locations. Recognition units 410a, 410d and 410e each
have an input coupled signal line 430 by signal line 630 for
receiving the image query. The recognition results from each of the
plurality of recognition units 410a-410e are sent via signal lines
636, 638, 640, 642 and 644 to the result combiner 610. The output
of the result combiner 610 is coupled to signal line 430.
[0095] In one embodiment, the recognition units 410a, 410b and 410c
cooperate together with index tables 1, 2 and 3, 412a-412c each
storing image features corresponding to the same pages but with
differing levels of blur caused by device and environmental
factors. For example, index table 1 412a may store image features
for pristine images of pages such as from a PDF document, while
index table 2 412b stores images of the same pages but with a first
level of blur and index table 3 412c stores images of the same
pages but with the second level of blur. In one embodiment, the
index tables 1, 2 and 3, 412a-412c are quantization trees. The
first recognition unit 410a receives the image query via signal
line 630. The first recognition unit 410a comprises an invisible
junction feature extractor 602 and a retriever 604a. The invisible
junction feature extractor 602 receives the image query, extracts
the invisible junction features and provides them to the retriever
604a. The retriever 604a uses the extracted invisible junction
features and compares them to the index table 1 412a. If the
retriever 604a identifies a match, the retriever 604a sends the
recognition results via signal line 636 to the result combiner 610.
If however, the retriever 604a was unable to identify a match or
identifies a match with low confidence, the retriever 604a sends
the extracted invisible junction features to the retriever 604b of
the second recognition unit 410b via signal line 632. It should be
noted that since the invisible junction features have already been
extracted, the second recognition unit 410b does not require an
invisible junction feature extractor 602. The second recognition
unit 410b performs retrieval functions similar to the first
recognition unit 410a, but cooperates with index table 2 412b that
has invisible junction features for slightly blurry images. If the
retriever 604b identifies a match, the retriever 604b sends the
recognition results via signal line 638 to the result combiner 610.
If the retriever 604b of the second recognition unit 410b is unable
to identify a match or identifies a match with low confidence, the
retriever 604b sends the extracted invisible junction features to
the retriever 604c of the third recognition unit 410c via signal
line 634. The retriever 604c then performs a similar retrieval
function but on index table 3 412c. Those skilled in the art will
understand that while one pristine set of images and two levels of
blur are provided, this is only by way of example and that any
number of additional levels of blur from 0 to n may be used.
[0096] The recognition units 410d and 410e operate in parallel with
the other recognition units 410a-c. The fourth recognition unit
410d comprises a brick wall coding feature extractor 606 and a
retriever 604d. The brick wall coding feature extractor 606
receives the image query and bounding boxes, parses the bounding
boxes and generates brick wall coding features. These brick wall
coding features are provided to the retriever 604d and the
retriever 604d compares them to the features stored in index table
4 412d. In one embodiment, index table 4 412d is a hash table. The
retriever 604d identifies any matching pages and returns the
recognition results to the result combiner 610 via signal line 642.
The fifth recognition unit 410e operates in a similar manner but
for path coding. The fifth recognition unit 410e comprises a path
coding feature extractor 608 and a retriever 604e. The path coding
feature extractor 608 receives the image query and bounding boxes,
parses the image and generates path coding features that are
provided to the retriever 604e and the retriever 604e compares them
to features stored in the index table 5 412e. In one embodiment,
the index table 5 412e is a SQL database of character strings. The
retriever 604e identifies any matching strings and returns the
recognition results to the result combiner 610 via signal line
644.
[0097] The result combiner 610 receives recognition results from
the plurality of recognition units 410a-e and produces one or a
small list of matching results. In one embodiment, each of the
recognition results includes an associated confidence factor. In
another embodiment, context information such as date, time,
location, personal profile or retrieval history are provided to the
result combiner 610. These confidence factors along with other
information are used by the result combiner 610 to select the
recognition results most likely to match the input image query.
Image Registration Unit 408
[0098] FIG. 7 shows an embodiment of the image registration unit
408. The image registration unit 408 comprises a blurry generator
702, a plurality of invisible junction feature extractors 704a-c, a
plurality of invisible junction index table updaters 706a-c, a
brick wall coding feature extractor 708, a brick wall coding index
table updater 710, a path coding feature extractor 712, a path
coding index table updater 714 and a plurality of master index
tables 416a-e. The image registration unit 408 also includes other
control logic (not shown) that controls the updating of the working
index tables 412 from the master index table 416. The image
registration unit 408 can update the index tables 412 of the
acquisition unit 406 in a variety of different ways based on
various criteria such performing updates on a periodic basis,
performing updates when new content is added, performing updates
based on usage, performing updates for storage efficiency, etc.
[0099] The blurry generator 702 has an input coupled in signal line
730 to receive an image and a page identification number. The
blurry generator 702 has a plurality of outputs and each output is
coupled by signal lines 732, 734 and 736 to invisible junction
feature extractors 704a-c, respectively. The blurry generator 702
passes a pristine image and the page identification number to the
output and signal line 732. The blurry generator 702 then generates
an image with a first level of blurriness and outputs it and the
page identification number on signal line 734 to invisible junction
feature extractor 704b, and another image with a second level of
blurriness and outputs it and page identification number on signal
line 736 to invisible junction feature extractor 704c.
[0100] The invisible junction feature extractors 704 receive the
image and page ID, extract the invisible junction features from the
image and send them along with the page ID to a respective
invisible junction index table updater 706. The outputs of the
plurality of invisible junction feature extractors 704a-c are
coupled to input of the plurality of invisible junction index table
updaters 706a-c. For example, the output of invisible junction
feature extractor 704a is coupled to an input of invisible junction
index table updater 706a. The remaining invisible junction feature
extractors 704b-c are similarly coupled to respective invisible
junction index table updaters 706b-c. The invisible junction index
table updaters 706 are responsible for formatting the extracted
features and storing them in a corresponding master index table
416. While the master index table 416 is shown as five separate
master index tables 416a-e, those skilled in the art will recognize
that all the master index tables could be combined into a single
master index table or into a few master index tables. Once the
invisible junction index table updaters 706 have stored the
extracted features in the index table 416, they issue a
confirmation signal that is sent via signal lines 740 and 136 back
to the MMR publisher 108.
[0101] The brick wall coding feature extractor 708 and the path
coding feature extractor 712 operate in a similar fashion and are
coupled to signal line 738 to receive the image, a page
identification number and bounding box information. The brick wall
coding feature extractor 708 extracts information from the input
needed to update its associated index table 416d. The brick wall
coding index table updater 710 receives the extracted information
from the brick wall coding feature extractor 708 and stores it in
the index table 416d. The path coding feature extractor 712 and the
path coding index table updater 714 operate in a like manner but
for path coding. The path coding feature extractor 712 also
receives the image, a page number and bounding box information via
signal line 738. The path coding feature extractor 712 extracts
path coding information and passes it to the path coding index
table updater 714. The path coding index table updater 714 stores
the information in index table 5 416e. The architecture of the
registration unit 408 is particularly advantageous because it
provides an environment in which the MMR publisher 108 can
automatically update the index tables simply by providing images
and page numbers to the image registration unit 408 and the index
tables are updated automatically.
MMR Publisher 108
[0102] An embodiment of the MMR publisher 108 is shown in FIG. 8.
The MMR publisher 108 comprises conventional publishing software
802, a pre-press software plug-in for registration and annotation
804, and a hotspot creator 806. The MMR publisher 108 is coupled to
signal line 138 to connect with the image registration unit 408 and
the hotspot database 404 (such as via server 302).
[0103] The conventional publishing software 802 is software for
creating digital content including text, graphics, and pictures.
Examples of the conventional publishing software used in the
production and distribution of newspapers include Adobe Acrobat
manufactured and sold by Adobe Inc. of San Jose, Calif. or
QuarkXPress manufactured and sold by Quark, Inc. of Denver, Colo.
The conventional publishing software 802 may be other types of
proprietary software owned by large publishing companies.
[0104] The pre-press plug-in for registration and annotation 804 is
software and routines for interfacing with the conventional
publishing software 802 and generating additional information used
by the image registration unit 408 so that the content can be
automatically uploaded to the acquisition unit 406. For example,
the prepress plug-in for registration and annotation communicates
and interfaces with the image registration unit 408 to maintain a
unique page identification numbering system that is consistent
across image pages generated by the conventional publishing
software 802, the image pages stored in the master index table 416,
and the page numbers used in referencing data in the hotspot
database 404. The prepress plug-in for registration 804 also
generates bounding boxes for image pages generated by the
conventional publishing software 802; the bounding boxes are
subsequently used by the image registration unit 408 for certain
types of encoding. The pre-press plug-in for registration and
annotation 804 also analyzes the images provided by the
conventional publishing software 802 and ensures that the files are
of a type usable by the feature extractors 704, 708, 712.
[0105] The hotspot creator 806 is an authoring tool for creating
hotspots. Hotspots identify the (x,y) coordinates of polygons on a
document image and links to electronic data such as URLs that are
associated with each polygon. In one embodiment, hotspots are
annotations in Acrobat PDF files that include the (x,y) coordinates
of polygons on a document and links to electronic data such as
URLs. The hotspot creator 806 can be used to create a hotspot (a
"hotspot" is a polygon on an image), associate the hotspot with a
particular page in a document, and a particular location on the
page, associate zero or more links with each hotspot, and generate
and send the hotspot files to the server 302 for storage in the
hotspot database 404. A hotspot file lists each hotspot, the
coordinates of its polygon, and any links associated with it. The
hotspot file can be saved as a separate file or equivalently the
same data can be embedded in the document source file. The hotspot
creator 806 can be a stand-alone software application that reads a
source document such as Word, PDF, or an image format such as tiff,
and provides a user interface that lets the user draw polygons on
the document, add links to each of the hotspots, and save the
hotspot files. The hotspot creator 806 can also be packaged as a
plug-in for existing document authoring applications such as Word,
Acrobat, Quark Express, etc. and can be designed so that the user
can define polygons on the document, add links, and save the
hotspot files (or, equivalently the source file with the hotspot
data embedded in it). The hotspot creator 806 can also be packaged
as a software application that extracts links from existing
documents and saves them in the hotspot file. For example,
annotations in PDF files that include polygon coordinates and links
to electronic data can be removed from the PDF and saved separately
in a hotspot file. The hotspot creator 806 also allows the
publisher 108 to allow preferences to be associated with the
hotspot locations.
Methods
[0106] FIG. 9 is a flowchart of a general method for generating and
sending a retrieval request and processing the retrieval request
with an MMR system 100. The method begins with the mobile device
102 capturing 902 an image. A retrieval request that includes the
image, a user identifier, and other context information is
generated by the mobile device 102 and sent 904 to the MMR gateway
104. The MMR gateway 104 processes 906 the retrieval request by
extracting the user identifier from the retrieval request and
verifying that it is associated with a valid user. The MMR gateway
104 also performs other processing such as recording the retrieval
request in the log 310, performing any necessary accounting
associated with the retrieval request and analyzing any MMR
analytics metrics. Next, the MMR gateway 104 generates 908 an image
query and sends it to the dispatcher 402. The dispatcher 402
performs load-balancing and sends the image query to the
acquisition unit 406. In one embodiment, the dispatcher 402
specifies the particular recognition unit 410 of the acquisition
unit 406 that should process the image query. Then the acquisition
unit 406 performs 912 image recognition to produce recognition
results. The recognition results are returned 914 to the dispatcher
402 and in turn the MMR gateway 104. The recognition results are
also used to retrieve 916 hotspot data corresponding to the page
and location identified in the recognition results. Finally, the
hotspot data and the recognition results are sent 918 from the MMR
gateway 104 to the mobile device 102.
[0107] Referring now to FIG. 10, a method for registration of
images will be described. The method begins by generating 1002
images by using conventional publishing software 802. The images
are then augmented 1004 with bounding boxes, hotspot data and page
identification numbers using the prepress plug-in for registration
and annotation 804. The augmented images are then sent 1006 to the
MMR gateway 104. The MMR gateway 104 extracts the hotspot data and
adds it to the hotspot database 404. The MMR gateway 104 then sends
1008 the image, page number and bounding boxes to the image
registration unit 408. In an alternate embodiment as depicted in
FIG. 10 by the dashed line, the augmented images can be sent to the
image registration unit 408 without going through the MMR gateway
104. The indexing unit 414 and then performs 1010 feature
extraction on the images. Depending on the embodiment, feature
extraction may be performed for a single recognition algorithm,
multiple different recognition algorithms or the same recognition
algorithm on different data sets. The features extracted from step
1010 are then used to update 1012 the master index table(s) 416a-e.
Finally, the changes that were applied to the master index table(s)
416a-e are migrated 1014 to working index tables 412a-n of the
acquisition unit 406. This method is particularly advantageous
because images need only be provided to the image registration unit
408 and the image registration unit 408 automatically updates the
master index table 416, and automatically migrates the changes to
the working index tables 412 of the acquisition unit 406.
[0108] FIG. 11A illustrates a block diagram of MMR components in
accordance with one embodiment of the present invention. The
primary MMR components include a computer 1102 with an associated
printer 1 104.
[0109] The computer 1102 is any standard desktop, laptop, or
networked computer, as is known in the art. In one embodiment, the
computer is associated with publisher 108 as described in
conjunction with to FIG. 1. Printer 1104 is any standard home,
office, or commercial printer, as described herein. Printer 1104
produces printed document 1106, which is a paper document that is
formed of one or more printed pages.
[0110] The computer 1102 further comprises a variety of components,
some or all of which are optional according to various embodiments.
In one embodiment, the computer 1102 comprises source files 1108,
document authoring application 1110, plug-in 1112, GDI 1114,
printer driver 1116, data store 1118, and MMR printing software
1120.
[0111] Source files 1108 are representative of any source files
that are an electronic representation of a document. Example source
files 1108 include hypertext markup language (HTML) files,
Microsoft.RTM. Word.RTM. files, Microsoft.RTM. PowerPoint.RTM.
files, QuarkXpress files, simple text files, portable document
format (PDF) files, and the like. As described herein, documents
received at document authoring application 1110 originate from
source files 1108 in many instances. In one embodiment, source
files 1108 are stored on the hard drive of computer 1102.
[0112] Document authoring application 1110 is an application that
provides for authoring and editing of documents. Document authoring
application 1110 may be any application that allows for authoring
and editing of documents, such as Microsoft Word, Adobe Acrobat,
Internet Explorer, and Quark Xpress. In one embodiment, the
document authoring application 1110 may be used to retrieve
documents from the source files 1108.
[0113] Plug-in 1112 is a software application that provides an
authoring function. Plug-in 1112 may run in document authoring
application 1110, or alternatively may be a standalone software
application. Plug-in 1112 performs various transformations and
other modifications to documents or web pages displayed by document
authoring application 1110 according to various embodiments. For
example, plug-in 1112 may surround symbolic data, or hotspot,
designations with uniquely identifiable fiducial marks in a
special, invisible font.
[0114] In one embodiment in which the document authoring
application 1110 is the Internet Explorer browser, the plug-in 1112
modifies the Document Object Model (DOM) for a web page in the
browser by adding SPAN element fiducial marks to the .html document
associated with the web page that do not affect the layout of the
web page. An example of a fiducial mark 1202 is shown in FIG. 12.
Fiducial identification 1204 specifies a fiducial type (b=begin,
e=end, t=text, i=image) and a number identifying the associated
URL. The position: absolute attribute 1206 ensures that the element
does not affect the flow of the document. The text-decoration: none
attribute 1208 ensures that the fiducial text does not get
underlined. The font-family: `ExportToPaper Courier new` attribute
1210 specifies a font that is based on the Courier font, but that
does not have any glyphs. Thus, the fiducials do not appear on the
screen, but still get sent to, and can be detected by, the printer
driver 1116. An abbreviated form of the fiducial marks, <SPAN .
. . >t0</SPAN>, is used herein. FIGS. 14A and 14B show a
link before 1402 and after fiducials are added 1404.
[0115] Although this example uses Internet Explorer (browser) as
the document authoring application 1110. However, in other
embodiments, other document authoring applications 1110 may be
used, with similar processes. For example, many such document
authoring applications 1110 provide the ability to incorporate
custom-designed plug-ins that run in conjunction with the existing
software. Such as plug-in could be sued to add instructions that
embed font change commands that add "bn" and "en" tags at the
beginning and end of each word in the invisible font as described
in the Internet Explorer example above. As in the example, the
intermediate .xml files would be produced including unique
identifiers that could be matched to their locations as provided by
the print driver as described herein, to determine the locations of
bounding boxes around words.
[0116] Plug-in 1112 also may perform other functions, such as
creating symbolic hotspot descriptions (symb_hotspot.xml) as
described herein.
[0117] Printer driver 1116 is software and routines for performing
a feature extraction and/or coordinate capture on the printed
representation of documents, so that the layout of characters and
graphics on the printed pages can be retrieved. The layout, i.e.,
the two-dimensional arrangement of text on the printed page, may be
captured automatically at the time of printing by the printer
driver 1116. For example, printer driver 1116 executes all the text
and drawing print commands and, in addition, intercepts and records
the x,y coordinates and other characteristics of every character
and/or image in the printed representation. According to one
embodiment, printer driver 1116 includes a Printcapture DLL as
described herein, a forwarding Dynamically Linked Library (DLL)
that forwards calls of an existing DLL while capturing information
from the calls. A more detailed description of the functionality of
the print capture DLL is described in reference to FIG. 18. Those
skilled in the art will recognize that the printer driver 1116 is
coupled to the output of document authoring application 1110 for
capture of data.
[0118] Data store 1118 is any database known in the art for storing
files, modified for use with the methods described herein. For
example, according to one embodiment data store 1118 stores source
files 1108, symb_hotspot.xml, page_desc.xml, rendered page layouts,
imaged documents, hot spot definitions, and feature
representations.
[0119] MMR printing software 1120 is software and routines that
facilitate the MMR printing operations described herein, for
example as performed by the components of computer 1102 as
previously described. MMR printing software 1120 is described below
in greater detail with reference to FIG. 11B.
[0120] FIG. 11B illustrates a set of software components included
in MMR printing software 1120 in accordance with one embodiment of
the invention. It should be understood that all or some of the MMR
printing software 1120 may be included in the computer 1102, mobile
device 102, or publisher 108. While the MMR printing software 1120
will now be described as including these different components,
those skilled in the art will recognize that the MMR printing
software 1120 could have any number of these components from one to
all of them. The MMR printing software 1120 includes a conversion
module 1130, an embed module 1132, a parse module 1134, a transform
module 1136, a feature extraction module 1138, a hotspot module
1140, a render/display module 1142, and a storage module 1144.
[0121] Conversion module 1130 is software and routines for
conversion of a source document, e.g. from source files 1108, into
an imaged document from which a feature representation can be
extracted.
[0122] Embed module 1132 is software and routines for enabling
embedding of fiducial marks, e.g., as described above,
corresponding to a designation for a hotspot in an electronic
document. In one particular embodiment, the embedded fiducial marks
indicate a beginning point for the hotspot and an ending point for
the hotspot.
[0123] Parse module 1134 is software and routines for enabling
parsing an electronic document (that has been sent to the printer
1104) for a fiducial mark indicating a beginning point for a
hotspot.
[0124] Transformation module 1136 is software and routines for
enabling application of a transformation rule to a portion of an
electronic document. In one particular embodiment, the portion is a
stream of characters between a fiducial mark indicating a beginning
point for a hotspot and a fiducial mark indicating an ending point
for the hotspot.
[0125] Feature extraction module 1138 is software and routines for
enabling the extraction of features and capture of coordinates
corresponding to a printed representation of a document and a
hotspot. Coordinate capture includes tapping, or intercepting,
print commands using a forwarding dynamically linked library and
parsing the printed representation for a subset of the coordinates
corresponding to a hotspot or transformed characters. Feature
extraction module 1138 enables the functionality of printer driver
1116 according to one embodiment.
[0126] Hotspot module 1140 is software and routines for enabling
association of one or more clips with one or more hotspots. Hotspot
module 1140 also enables formulation of a hotspot definition by
first designating a location for a hotspot within a document and
defining a clip to associate with the hotspot.
[0127] Render/display module 1142 is software and routines for
enabling a document or a printed representation of a document to be
rendered or displayed.
[0128] Storage module 1144 is software and routines for enabling
storage of various files, including a page layout, an imaged
document, a hotspot definition, and a feature representation.
[0129] The software portions 1130-1144 need not be discrete
software modules. The software configuration shown is meant only by
way of example; other configurations are contemplated by and within
the scope of the present invention, as will be apparent in light of
this disclosure.
[0130] Referring now to FIG. 13, a flowchart is show for a method
of capturing symbolic information about a document in accordance
with one embodiment of the present invention. The method begins
with the plug-in 1112 to the document authoring application 1110
modifying 1302 the data sent to the GDI uniquely identifying a
piece of symbolic data using an invisible font. For example,
fiducial marks are inserted surrounding each piece of symbolic
data. The marks are in a font that is similar to Courier but has no
glyphs, so they are not visible and do not modify the printed
document in any way, but can be detected in print commands.
[0131] Referring to FIG. 14A, an original HTML page is shown. FIG.
14B shows the same HTML after the fiducial marks have been added.
FIG. 14C shows a 24 bpp 600 raster image of the page. In addition,
the plug-in 1112 creates 1308 a symbolic hotspot description
(symb_hotspot.xml). symb_hotspot.xml is an extensible markup
language ("XML") file generated by plug-in 1112 that identifies a
hotspot within a document. symb_hotspot.xml identifies the hotspot
number and content, and may be stored to data store 1118. An
example of a symbolic hotspot description is shown in FIG. 15.
[0132] In response to a print command, coordinates corresponding
the printed representation and the hotspot are captured. In one
embodiment, a printer driver 1116 "taps" text and drawing commands
within a print command. The printer driver 1116 executes all the
text and drawing commands and, in addition, intercepts and records
1304 the x,y coordinates and other characteristics of every
character and/or image in the printed representation. This step is
described in greater detail in conjunction with FIG. 18. In the
process of capturing the coordinates for the printed
representation, the symbolic data locations are easily identified
using the embedded fiducial marks in the HTML. For example, when
the begin mark is encountered, the x,y location is recorded of all
characters until the end mark is found.
[0133] The locations are saved 1306 as a page description file
(page_desc.xml). page_desc.xml 1304 is an XML file created by the
printer driver 1115 to which text-related output is written for
function calls that are text related. page_desc.xml 1304 includes
coordinate information for a document for all printed text by word
and by character, as well as hotspot information, printer port
name, browser name, date and time of printing, and dots per inch
(dpi) and resolution (res) information. page_desc.xml 1304 is
stored, e.g., in data store 1118. FIGS. 16A-16E illustrate in
greater detail an example of a page_desc.xml 1304 for the HTML file
of FIG. 14A.
[0134] Finally, page_desc.xml and symb_hotspot.xml are merged 1310
into hotspot.xml, which is an XML file that is created when a
document is printed. hotspot.xml includes hotspot identifier
information such as hotspot number, coordinate information,
dimension information, and the content of the hotspot. An example
of a hotspot.xml file is illustrated in FIG. 17.
[0135] FIG. 18 shows how the GDI 1114 interacts with the printer
driver 1116 when a document is printed. In conventional processing,
the printer driver is comprised of a set of dynamically linked
libraries (DLLs). The printer graphics dll is the one that receives
instructions from the GDI. When an application that prints a
document calls the CreateDC function to create a printer device
context, the GDI checks to see if the appropriate printer graphics
DLL is loaded. If it is not, the GDI loads the DLL and calls the
DrvEnableDriver function in the DLL.
[0136] Next, the GDI calls the printer graphics DLL's DrvEnablePDEV
function so the driver can create a physical device instance and
return device characteristics. GDI uses the returned information to
create an internal description of the device instance.
[0137] The GDI then calls the printer graphics DLL's
DrvCompletePDEV function to supply a GDI handle to the device
instance. The graphics DLL must use this handle as input to some of
the Eng-prefixed callbacks provided by the GDI drawing engine.
[0138] After the GDI receives the device instance handle, it then
makes a call to the graphics DLL's DrvEnableSurface function, which
sets up the surface for drawing, and associates it with the
physical device instance.
[0139] After this, for each document to be printed, the GDI calls
DrvStartDoc in the printer graphics DLL. Then for each physical
page, it calls DrvStartPage at the beginning of each page and
follows that with a number of Drv-prefixed calls that render text,
graphics and bitmap images on the page. At the end of the page, the
GDI calls DrvSendPage and DrvEndDoc. A number of other Eng-prefixed
commands are also provided.
[0140] Note that in FIG. 18 an additional DLL, a Printer Capture
DLL 1802 is placed before the normal printer graphics DLL 1804. The
Print Capture DLL 1802 is a forwarding dll. This means that a tap
has been placed on some incoming DrvXXX calls before (or after)
they are forwarded to the printer graphics DLL 1804. The printer
graphics DLL 1804 actually implements the functionality for the
DrvXXX call. This Print Capture DLL 1802 simply monitors the
incoming calls, captures information about them, and forwards the
call to the printer graphics DLL 1804. The Print Capture DLL 1802
also executes its own code for some of the DrvXXX calls, if
necessary to create the raster images or symbolic description. In
our case, the symbolic description (symb_hotspot.xml) is
information about objects on the document, such as the x,y location
of characters, vector graphics, or bitmap images. Table 1 shows the
DrvXXX calls that are executed in the Print Capture DLL 1802.
TABLE-US-00001 TABLE 1 DrvXXX commands implemented in the Print
Capture DLL DrvEnablePDEV DrvDisablePDEV DrvEnableSurface
DrvDisableSurface DrvStartDoc DrvEndDoc DrvStartPage DrvEndPage
DrvTextOut DrvBitBlt DrvStretchBlt DrvCopyBits DrvStretchBltROP
DrvAlphaBlend DrvTransparentBlt DrvPlgBlt DrvGradientFill DrvLineTo
DrvFillPath DrvStrokeAndFillPath DrvStrokePath
DrvDeleteBitmapSURFOBJ DrvCreateBitmapSURFOBJ DrvGetBmpDelta
[0141] When the Print Capture DLL 1802 receives a DrvEnablePDEV
call, in addition to passing it on to the printer graphics DLL
1804, it creates a PDEVMonitorDoc object. The PDEVMonitorDoc object
contains raster images that are written to when certain DrvXXX
calls are received and it maintains symbolic descriptions of
certain page content, such as the positions of objects on the page.
When a command is received by the printer driver that indicates the
page should be printed, the Print Capture DLL 1802 calls a function
that saves the raster image of the page.
[0142] A Printer Device Context (PDEV) encapsulates a target for
drawing as well as drawing settings like font, color, etc. In the
Print Capture DLL 1802, the function that creates a PDEV also
creates the PDEVMonitorDoc. The PDEVMonitorDoc creates memory
buffers and attaches them to the associated PDEV as secondary
surfaces. Whenever a command (DrvTextOut( ), DrvBitBlt( ), etc. is
received by the Print Capture DLL 1802, the command is not only
forwarded to the printer graphics DLL 1804, but also performed upon
the memory buffers owned by the PDEVMonitorDoc. This means that
whatever is being drawn to the printer also gets drawn to a memory
buffer on the local computer. When a command is received by the
printer driver that indicates the page should be printed, the
contents of the memory buffer are compressed and written out in JPG
and PNG format.
[0143] The Print Capture DLL 1802 includes code for all text
drawing functions. This means for applications that use the
text-drawing GDI functions coordinate information for all printed
text can also be captured. This information is recorded in an XML
file that is stored with the JPGs/PNGs of the print operation.
[0144] FIG. 19 shows a flowchart of the process used by the print
capture DLL 1802 in accordance with one embodiment of the present
invention. The Print Capture DLL 1802 receives 1902 all function
calls directed to the printer driver 1116. It first checks 1904
whether the received call is one of the function calls it monitors.
These are functions that affect the appearance of a printed page in
some way. If the received call is not a monitored function call,
the call bypasses steps 1906-1914, and is forwarded 1916 to pass
the function call on to the printer graphics DLL 1804.
[0145] If it is a monitored function call, the method next
determines 1906 whether the function call specifies a new printer
device context. This is determined by checking the PDEV against an
internal device context table. A PDEV encapsulates a target for
drawing (which could be a printer, a memory buffer, etc.), as
previously noted, as well as drawing settings like font, color,
etc. All drawing operations (e.g., LineTo( ), DrawText( ), etc) are
performed upon a device context. If the PDEV is not new, then a
memory buffer already exists that corresponds with the printer DC,
and step 1908 is skipped. If the PDEV is new, a memory buffer of
the same dimensions is created 1908 and attached to the PDEV as a
secondary surface.
[0146] The print capture DLL next determines 1910 whether the call
is a text-related function call. If it is not, step 1912 is
skipped. If the function call is text-related, the text-related
output is written 4430 to an xml file, referred to herein as
page_desc.xml.
[0147] Referring again to FIG. 19, following the determination that
the call is not text related, or following writing 1912 the
text-related output to page_desc.xml, the print capture DLL 1802
executes 1914 the function call on the memory buffer for the PDEV.
Then, all the monitored function calls are passed on to the printer
graphics DLL 1804 as if the printer capture DLL 1802 was not
present.
[0148] The foregoing description of the embodiments of the present
invention has been presented for the purposes of illustration and
description. It is not intended to be exhaustive or to limit the
present invention to the precise form disclosed. Many modifications
and variations are possible in light of the above teaching. It is
intended that the scope of the present invention be limited not by
this detailed description, but rather by the claims of this
application. As will be understood by those familiar with the art,
the present invention may be embodied in other specific forms
without departing from the spirit or essential characteristics
thereof. Likewise, the particular naming and division of the
modules, routines, features, attributes, methodologies and other
aspects are not mandatory or significant, and the mechanisms that
implement the present invention or its features may have different
names, divisions and/or formats. Furthermore, as will be apparent
to one of ordinary skill in the relevant art, the modules,
routines, features, attributes, methodologies and other aspects of
the present invention can be implemented as software, hardware,
firmware or any combination of the three. Also, wherever a
component, an example of which is a module, of the present
invention is implemented as software, the component can be
implemented as a standalone program, as part of a larger program,
as a plurality of separate programs, as a statically or dynamically
linked library, as a kernel loadable module, as a device driver,
and/or in every and any other way known now or in the future to
those of ordinary skill in the art of computer programming.
Additionally, the present invention is in no way limited to
implementation in any specific programming language, or for any
specific operating system or environment. Accordingly, the
disclosure of the present invention is intended to be illustrative,
but not limiting, of the scope of the present invention, which is
set forth in the following claims.
* * * * *